Bruno Pelletier
Cited by
Cited by
Kernel density estimation on Riemannian manifolds
B Pelletier
Statistics & probability letters 73 (3), 297-304, 2005
Atmospheric correction of satellite ocean-color imagery during the PACE era
RJ Frouin, BA Franz, A Ibrahim, K Knobelspiesse, Z Ahmad, B Cairns, ...
Frontiers in Earth Science 7, 145, 2019
On the estimation of the gradient lines of a density and the consistency of the mean-shift algorithm
E Arias-Castro, D Mason, B Pelletier
The Journal of Machine Learning Research 17 (1), 1487-1514, 2016
Retrieving of particulate matter from optical measurements: A semiparametric approach
B Pelletier, R Santer, J Vidot
Journal of Geophysical Research: Atmospheres 112 (D6), 2007
Non-parametric regression estimation on closed Riemannian manifolds
B Pelletier
Journal of Nonparametric Statistics 18 (1), 57-67, 2006
A graph-based estimator of the number of clusters
G Biau, B Cadre, B Pelletier
ESAIM: Probability and Statistics 11, 272-280, 2007
Exact rates in density support estimation
G Biau, B Cadre, B Pelletier
Journal of Multivariate Analysis 99 (10), 2185-2207, 2008
Bayesian methodology for inverting satellite ocean-color data
R Frouin, B Pelletier
Remote Sensing of Environment 159, 332-360, 2015
Remember the curse of dimensionality: The case of goodness-of-fit testing in arbitrary dimension
E Arias-Castro, B Pelletier, V Saligrama
Journal of Nonparametric Statistics 30 (2), 448-471, 2018
The normalized graph cut and Cheeger constant: from discrete to continuous
E Arias-Castro, B Pelletier, P Pudlo
Advances in Applied Probability 44 (4), 907-937, 2012
A kernel-based classifier on a Riemannian manifold
JM Loubes, B Pelletier
Statistics & Decisions 26 (1), 35-51, 2008
Estimation of density level sets with a given probability content
B Cadre, B Pelletier, P Pudlo
Journal of Nonparametric Statistics 25 (1), 261-272, 2013
Asymptotic normality in density support estimation
G Biau, B Cadre, D Mason, B Pelletier
Informative barycentres in statistics
B Pelletier
Annals of the Institute of Statistical Mathematics 57, 767-780, 2005
On the Convergence of Maximum Variance Unfolding.
E Arias-Castro, B Pelletier
Journal of Machine Learning Research 14 (7), 2013
Maximum entropy solution to ill-posed inverse problems with approximately known operator
JM Loubes, B Pelletier
Journal of Mathematical Analysis and Applications 344 (1), 260-273, 2008
Perturbation bounds for procrustes, classical scaling, and trilateration, with applications to manifold learning
E Arias-Castro, A Javanmard, B Pelletier
Journal of machine learning research 21, 2020
Operator norm convergence of spectral clustering on level sets
B Pelletier, P Pudlo
The Journal of Machine Learning Research 12, 385-416, 2011
Remote sensing of phytoplankton chlorophyll-a concentration by use of ridge function fields
B Pelletier, R Frouin
Applied optics 45 (4), 784-798, 2006
On the estimation of latent distances using graph distances
E Arias-Castro, A Channarond, B Pelletier, N Verzelen
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